Aside from the books being studied, it seems that quantitative methods and literary studies have little in common. The former utilize a narrow approach, specified data, and techniques independent of the books themselves (ie. math); the later relies on conjecture. Comparing the two feels like looking at apples and oranges–while both are fruits, their particular distinctions greatly overshadow their limited similarities.
Ultimately though, it does seem poignant to remember the close dependence of both quantitative methods and literary studies on variables like time, environment, technology, ect. This shared history critically shapes the circumstances of both approaches, however, the efforts of each in reaction are highly different. Quantitative methods, whether empirical or derived, function under the direct presence (and often absence) of data. As Weedon and Eliot both recognize, these data sets available are often insufficient. Time and loss challenge the data of book history, and as such quantitative methods have turned to narrower data sets and studies that can be more assuredly relied on. It is this ‘material’ world (coined by Eliot), though riddled with its own scope of inconsistencies in fact, from which a more accurate understanding of book history can be made. While such a rationalized perspective is probably best attributed to the passage of time Weedon/Eliot have, I found their more realistic favorable to the broad, and overreaching claims of Febre, Martin, and Darnton. Unlike quantitative methods, in the face of historical variables, literary studied have turned to guess.
It’s as Eliot says, “I needed to see the forest, not a host of additional trees” (285). After the passage of time, the destruction of texts/records, and the basic uncertainty of history, it is seemingly impossible to ‘recreate this forest’. Although both quantitative methods and literary studies rightfully recognize the interdisciplinary nature of this forest, the trees have been cleared for both. It is only quantitative methods of book history though, that have looked to supplement this absence. Quantitative methods focus on actual data available, and although this pool is ever-changing (technology, discoveries, ect.), it has always been more consistent than the claims made in literary studies like Sociology of Text, Annales School, or Communication Circuit. These literary studies rely on uncertainties–authorial intent, context of place and person, culture. Although arguably more entertaining and flashy than quantitative methods (even Eliot and Miller admit the oft boring practice of collecting and analyzing data), literary study will never have the same verified credibility that the more recent field of quantitative methods allot to the ‘history of the book’. I’m curious to see how the two approaches to the history of books interact throughout the rest of this course (if at all).
Finally, as an aside, I am curious how quantitative methods manipulate data to the interests of their studies. Eliot remarks that data sets are categorized, simplified, and ordered (291). Weedon similarly offers many quantitative methods, each of which can be applied to a specific scenario and data set. These techniques reminded me of the practices of the bestseller lists we first looked at. In both, the data seems manipulated for some purpose. I’m curious if quantitative methods have applied this manipulation out of necessity, or intent? To me, this paradox seems to lean toward necessity, but I am curious to see what others think.